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Network Appliance NetApp Certified AI Expert Sample Questions:
1. An MLOps engineer is troubleshooting a failed Kubeflow pipeline step. The step was designed to create a clone of a dataset for a training job using the NetApp DataOps Toolkit. The pod logs for the failed pipeline step show the following:
Traceback (most recent call last):
File "create_clone.py", line 15, in <module>
clone_pvc(source_pvc_name="training-data-v2", new_pvc_name="train-job-34a-data") NameError: name 'clone_pvc' is not defined The engineer reviews the Python script for the pipeline step:
# create_clone.py
import os
from netapp_dataops.k8s import create_pvc
# Other code
print("Cloning source dataset for training run...")
clone_pvc(
source_pvc_name="training-data-v2",
new_pvc_name="train-job-34a-data"
)
print("Clone created successfully.")
What is the cause of the error?
A) The Python script is attempting to use the 'clone_pvc' function, but it was not imported from the
'netapp_dataops.k8s' library.
B) The NetApp DataOps Toolkit is not installed in the container image used for this pipeline step.
C) The Kubernetes cluster is not running NetApp Trident.
D) The source PVC 'training-data-v2' does not exist.
2. Which of the following platforms provides tools for model training and deployment specifically for AI workloads?
A) All of the above
B) Google VertexAI
C) RunAI
D) Domino Data Labs
3. An organization's AI platform team needs to provide two distinct tiers of storage for their data scientists on a single Kubernetes cluster:
1. 'gold-tier': Extremely low-latency storage for active model training, using an all-flash NetApp ASA system.
2. 'bronze-tier': Cost-effective, high-capacity storage for data staging and archiving, using a NetApp StorageGRID system.
How should the platform team configure NetApp Trident to meet these requirements? (Select all that apply.)
A) Create a single StorageClass named 'multi-tier-storage' that references both backends.
B) Configure the 'bronze-tier' StorageClass to reference the StorageGRID backend.
C) Create a single Trident backend that points to both the ASA and StorageGRID systems simultaneously.
D) Create two separate Trident backend configurations, one for the ASA ('backend-asa.yaml') and one for StorageGRID ('backend-sgrid.yaml').
E) Configure the 'gold-tier' StorageClass to reference the ASA backend.
F) Create two distinct StorageClasses, 'gold-tier' and 'bronze-tier'.
4. An enterprise is planning a generative AI solution to power its internal support chatbot. The architect must choose between a RAG-based approach and fine-tuning a base model. The project stakeholders have provided a list of prioritized requirements.
| Requirement | Priority | Details
|
| | -- | |
| Factual Accuracy | Critical | Must use the latest product documentation, updated daily.
| | Brand Voice & Persona | High | Must respond in the company's specific, formal tone.
| | Development Cost | High | Limited budget for GPU compute hours for model training.
|
| Data Traceability | Critical | Must be able to cite the exact source document for each answer.
|
Which two recommendations should the architect make to best satisfy these requirements?
(Choose 2.)
A) Propose a hybrid approach where a base model is first lightly fine-tuned for persona, then used within a RAG system for factual grounding.
B) Use RAG exclusively, as prompt engineering alone can fully replicate a specific brand voice and persona.
C) Prioritize fine-tuning to embed the company's brand voice and persona into the model.
D) Recommend training a new LLM from scratch to ensure both brand voice and factual accuracy are built-in.
E) Prioritize a RAG architecture to meet the critical requirements for factual accuracy and data traceability.
5. The architect needs to design an efficient data flow to move curated training sets from the central StorageGRID data lake to the high-performance NetApp ASA system used by the AI cluster. The process must be manageable from a single interface and should be automatable. Which two NetApp technologies should be used to implement this data pipeline stage? (Choose 2.)
A) A custom Python script using the NetApp DataOps Toolkit to trigger the data movement.
B) A manual copy process using an S3 client on a bastion host.
C) NetApp SnapMirror to replicate data from the StorageGRID object store to the ASA's file system.
D) NetApp FabricPool to automatically tier the data from StorageGRID to the ASA.
E) NetApp BlueXP copy and sync service to create and manage the data synchronization relationship between the S3 source and the NFS/CIFS destination.
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: A | Question # 3 Answer: B,D,E,F | Question # 4 Answer: A,E | Question # 5 Answer: A,E |
